GC Enterprise Architecture/Framework/DataGuide
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Revision as of 15:22, 20 January 2022 by Maisha.abdullah (talk | contribs)
Information architecture[edit | edit source]
Information architecture includes both structured and unstructured data. The best practices and principles aim to support the needs of a business service and business capability orientation. To facilitate effective sharing of data and information across government, information architectures should be designed to reflect a consistent approach to data, such as the adoption of federal and international standards. Information architecture should also reflect responsible data management, information management and governance practices, including the source, quality, interoperability, and associated legal and policy obligations related to the data assets. Information architectures should also distinguish between personal and non‑personal data and information as the collection, use, sharing (disclosure), and management of personal information must respect the requirements of the Privacy Act and its related policies.
Collect data to address the needs of the users and other stakeholders[edit | edit source]
- assess data requirements‑based program objectives, as well users, business and stakeholder needs
How to achieve:
* Summarize how the architecture meets the data needs of the users and other key stakeholders including:
* How does the data asset contribute to outcomes/needs of the user and other stakeholders
* Gaps in the existing data assets to meet the needs of the users and other stakeholders and how the architecture addresses these gaps
* Gaps in data collection and analysis and how the architecture is addressing it so that department can ensure that we are serving the members of our society
* Alignment to the data foundation of the departmental information/data architecture practice
* Alignment to the theoretical foundation of the departmental information/data architecture practice
Tools:
* For Data Foundation – Implement:
* Data Catalogue
* Benefits Knowledge hub
* Data Lake (growth)
* Data Science and Machine Platform
* Stakeholder Requirements
* Solution Requirements
- collect only the minimum set of data needed to support a policy, program, or service
How to achieve:
* Summarize how the architecture aligns to “collect with a purpose” including:
* What is necessary (as opposed to what is sufficient) to meet the stakeholder need
* Supporting Performance Information Profiles (PIPs) used to assess a progress towards target and broader objectives
Tools:
* Value Stream (Value Item and Value Proposition – Context on What we measure)
* KPI Linked to benefits outcomes and objectives
- reuse existing data assets where permissible and only acquire new data if required
How to achieve:
* Summarize reusability of the architecture’s data assets given:
* Context of data assets and user and stakeholder needs
* Data quality and fit for purpose
* Privacy and Security Regulatory Framework
Tools:
* Legislative / Regulations
- ensure data collected, including from third-party sources, are of high quality
How to achieve:
* Summarize how the architecture meets the data quality requirements of third-party sources:
* Data quality meets fit for purpose
* Data quality dimensions including:
* Relevance,
* Timeliness
* Consistency,
* Reliability,
* Interpretability,
* Usability
* Data quality mechanism
Tools:
* Data Foundation – Implement (Leverage the standard definition)
* Data Catalogue
* Benefits Knowledge hub
* Data Lake (growth)
* Data Science and Machine Platform
Manage and reuse data strategically and responsibly[edit | edit source]
- define and establish clear roles, responsibilities, and accountabilities for data management
How to achieve:
* Summarize how the architecture assists in defining key data management roles and their responsibilities to ensure data is correct, consistent, and complete including:
* Identifies the data steward responsibilities;
* Identifies the data consumer responsibilities, and;
* Identifies the data custodian responsibilities.
Tools:
* Stakeholders
* Business Process Model
* Functional Requirements
* Business Glossary
- identify and document the lineage of data assets
How to achieve:
* Summarize how the architecture’s data assets demonstrate alignment with department's data governance and strategy including:
* Alignment to the data foundation of the ESDC information/data architecture practice
* Alignment to the theoretical foundation of the ESDC information/data architecture practice
Tools:
* Target state (solution data elements)
* Data Foundation – Implement (Leverage the standard definition)
* Data Catalogue
* Benefits Knowledge hub
* Data Lake (growth)
* Data Science and Machine Platform
* Theoretical Foundation
* EDRM (Conceptual and Logical)
* Business Glossary
* Departmental Data Strategy
- define retention and disposition schedules in accordance with business value as well as applicable privacy and security policy and legislation
How to achieve:
* Summarize for each key data assets:
* Retention and disposition schedules
* Disposition process
Tools:
* Target state (solution data elements)
* Non Functional Requirements
* IM Best Practices and Standards
- ensure data are managed to enable interoperability, reuse and sharing to the greatest extent possible within and across departments in government to avoid duplication and maximize utility, while respecting security and privacy requirements
How to achieve:
* Summarize how the architecture enables interoperability, reuse and sharing to the greatest extent possible within and across departments
* Summarize how the architecture avoids data duplication
Tools:
* Target State
* Data Foundation – Implement (Leverage the standard definition)
* Data Catalogue
* Benefits Knowledge hub
* Data Lake (growth)
- contribute to and align with enterprise and international data taxonomy and classification structures to manage, store, search and retrieve data
How to achieve:
* Summarize the alignment to departmental/GC:
* Data taxonomy structure
* Data classification structure
Tools:
* Data Foundation – Implement (Leverage the standard definition)
* Data Catalogue
* Theoretical Foundation
* EDRM (Conceptual and Logical)
* Business Glossary
[edit | edit source]
- share data openly by default as per the Directive on Open Government and Digital Standards, while respecting security and privacy requirements; data shared should adhere to existing enterprise and international standards, including on data quality and ethics
How to achieve:
* Summarize how the architecture supports sharing data openly by default as per Directive on Open Government and Digital Standards given:
* Existing departmental and GC data standards and policies
* International data standards; and the Privacy Act,
* Fitness for purpose
* Ethics
Tools:
* Data Foundation – Implement (Leverage the standard definition)
* Data Catalogue
* Benefits Knowledge Hub
* Data Lake (growth)
* Data Science and Machine Platform
* Theoretical Foundation
* EDRM (Conceptual and Logical)
* Business Glossary
* Departmental Data Strategy
- ensure data formatting aligns to existing enterprise and international standards on interoperability; where none exist, develop data standards in the open with key subject matter experts
How to achieve:
* Summarize how the architecture utilises existing enterprise and international data standards
* Summarize how the architecture has developed any data standards through open collaboration with key subject matter experts and the Enterprise Data Community of Practice.
Tools:
* Data Standards
* NIEM
* OpenData
* National Address Register
* Reference Data Repository
- ensure that combined data does not risk identification or re‑identification of sensitive or personal information
How to achieve: * Summarize how the architecture ensures the aggregation and combing of data does not pose a risk to information sensitivity or personal information
Design with privacy in mind for the collection, use and management of personal Information[edit | edit source]
- ensure alignment with guidance from appropriate institutional ATIP Office with respect to interpretation and application of the Privacy Act and related policy instruments
How to achieve: * Describe how the architecture aligns to guidance of the ATIP Office around personal information regulatory framework; policy framework; and consent directives
- assess initiatives to determine if personal information will be collected, used, disclosed, retained, shared, and disposed
How to achieve: * Has the initiative assessed if personal information will be collected, used, disclosed, retained, shared, and disposed
- only collect personal information if it directly relates to the operation of the programs or activities
How to achieve: * Summarize how the architecture ensures the personal information collected is directly required to the operational of the programs or activities
- notify individuals of the purpose for collection at the point of collection by including a privacy notice
How to achieve: * Does the solution’s privacy notice provide the purpose for collecting this personal information * Does the solution provide a privacy notice at the point of personal information collection
- personal information should be, wherever possible, collected directly from individuals but can be from other sources where permitted by the Privacy Act
How to achieve: * Does the architecture collect personal information directly from the individual * If no, what personal information is collect form other sources and does it comply with the Privacy Act and the consent directive of the source Tools: * Target State Architecture * Interim State Architecture
- personal information must be available to facilitate Canadians’ right of access to and correction of government records
How to achieve: * Summarize how the architecture facilitates Canadian's right to access their personal information records * Summarize how the architecture facilitates Canadian's right to correct their personal information records Tools: * Target State Architecture * Interim State Architecture
- design access controls into all processes and across all architectural layers from the earliest stages of design to limit the use and disclosure of personal information
How to achieve: * Summarize how the architecture limits the use and disclosure of personal information in accordance to the privacy legislative; policy frameworks and consent directives
- design processes so personal information remains accurate, up‑to‑date and as complete as possible, and can be corrected if required
How to achieve: * Summarize how the architecture ensures personal information remains accurate * Summarize how the architecture ensures personal information remains up-to-date * Summarize how the architecture ensures personal information remains complete as possible * Summarize how the architecture ensures personal information can be corrected if required Tools: * Non Functional Requirements * FUnctional Requirements
- de‑identification techniques should be considered prior to sharing personal information
How to achieve: * Outline the de-identification techniques used by the architecture in sharing personal information
- in collaboration with appropriate institutional ATIP Office, determine if a Privacy Impact Assessment (PIA) is required to identify and mitigate privacy risks for new or substantially modified programs that impact the privacy of individuals
How to achieve: * Describe how the architecture addresses the recommendations of the PIA * If not all recommendations of the PIA are being addressed, outline how the business will address any residual risks of the PIA
- establish procedures to identify and address privacy breaches so they can be reported quickly and responded to efficiently to appropriate institutional ATIP Office
How to achieve: * Are procedures established to identify and address privacy breaches * Summarize how the architecture enables/supports these procedures Tools: * Business Process Model
